Update README.md

README.md

@@ -1,8 +1,21 @@
+---
+license: mit
+datasets:
+- eriktks/conll2003
+language:
+- en
+base_model:
+- google-bert/bert-base-chinese
+pipeline_tag: token-classification
+library_name: transformers
+tags:
+- ner
+---
 # Model Card: BERT for Named Entity Recognition (NER)
 
 ## Model Overview
 
-This model, **sbert-conll-ner**, is a fine-tuned version of `bert-base-uncased` trained for the task of Named Entity Recognition (NER) using the CoNLL-2003 dataset. It is designed to identify and classify entities in text, such as **person names (PER)**, **organizations (ORG)**, **locations (LOC)**, and **miscellaneous (MISC)** entities.
+This model, **bert-conll-ner**, is a fine-tuned version of `bert-base-uncased` trained for the task of Named Entity Recognition (NER) using the CoNLL-2003 dataset. It is designed to identify and classify entities in text, such as **person names (PER)**, **organizations (ORG)**, **locations (LOC)**, and **miscellaneous (MISC)** entities.
 
 ### Model Architecture
 - **Base Model**: BERT (Bidirectional Encoder Representations from Transformers) with the `bert-base-uncased` architecture.
@@ -99,6 +112,4 @@ print(result)
 
 - **Transformers Library**: Hugging Face
 - **Dataset**: CoNLL-2003
-- **Base Model**: `bert-base-uncased` by Google
-
-
+- **Base Model**: `bert-base-uncased` by Google